Biology is entering an exciting era brought about by the increase in genome-wide information. As genome sequencing and high-throughput functional genomics approaches generate more and more data, researchers need new ways to tease out biological relevant information. Functional genomics in particular is making rapid progress in assigning biological meaning to genomic data. The information encoded in the genome comprises genes, the protein products of which mediate most of the functions in organisms, and control elements. Proteins were thought to be the most important effectors in the cells, although recently non-coding RNAs have also been identified as important players in regulatory processes.
Several key biological questions are central to continuing genome projects and are relevant to any cellular organism, from bacteria to humans. One challenge is to understand how genes that are encoded in a genome operate and interact to produce a complex living system. A related challenge is to determine the function of all the sequence elements in the genome. The toolbox of functional genomics has enabled several systematic approaches that can provide the answers to a few basic questions for the majority of genes in a genome, including when is a gene expressed, where its product is localized, with which other gene products does it interact and what phenotype results if a gene is mutated. Phenotypic analysis of mutants has been a powerful approach for determining gene function. Gene function can be altered through gene deletions, insertional mutagenesis and RNA interference (RNAi). RNAi is a relatively recent development for reducing gene expression. It follows reports of gene silencing in plants and other model organisms, and is based on the observation from C. elegans that adding double-stranded RNA (dsRNA) to cells often interferes with gene function in a sequence-specific manner. In many cases, the level of functional reduction cannot be adequately controlled, is incomplete, the level of specificity is not entirely predictable and in some organisms RNAi does not work (e.g. in the yeast Candida albicans).
It is obvious that functional genomics has changed the way biology is done and yet the field is still in its infancy in terms of detailing the complexity that underlies biological systems, such as the complex network of genetic regulation, protein interactions and biochemical reactions that make up a cell. Clearly there is a need to develop innovative technologies, especially in the field of functional proteomics, in order to accelerate discoveries and to maximize the potential offered by complementary methods in functional genomics. It would be desirable to possess a flexible technology that can directly target the biological function of a particular extracellular or intracellular protein instead of targeting the mRNA that translates it or manipulating the gene that encodes it.
The conversion of normally soluble proteins into conformationally altered insoluble proteins is thought to be a causative process in a variety of diseases such as for example the occurrence of amyloid beta peptide in Alzheimer's disease and cerebral amyloid angiopathy, alpha-synuclein deposits in Lewy bodies of Parkinson's disease, prions in Creutzfeldt-Jacob disease, superoxide dismutase in amyotrophic lateral sclerosis and tau in neurofibrillary tangles in frontal temporal dementia and Pick's disease. Thus far, protein aggregation has mainly been studied as an unwanted, disease-causing phenomenon and it is widely accepted that cross-beta mediated aggregation is the most frequently occurring and biologically relevant mechanism of aggregation2. Cross-beta aggregation is the term used to indicate that aggregation is nucleated via the formation of intermolecular beta-sheets to which each molecule in the aggregate contributes an identical strand of typically comprising at least three contiguous amino acids. There is now abundant data to show that the individual strands interact to form an intermolecular beta sheet and that this structure forms the backbone of the aggregate3,4. Self-association regions in target proteins can be determined by computer programs, such as TANGO6, which were developed for predicting the aggregation propensity of peptides and proteins. One specific form of aggregation, namely the highly ordered amyloid fibre, is already being explored in the art for potential use in the material sciences5. In addition, WO03102187 (Scegen, Pty Ltd) discloses a method for enhancing the activity of a molecule by fusing said molecule with a membrane translocating sequence, whereby the resulting chimeric molecule self-assembles into a higher molecular weight aggregate. US20050026165 (Areté Associates) discloses the use of conformational peptides, able to interact with the beta-sheet conformation of insoluble proteins such as prions, as a diagnostic tool for prion diseases.